Correlates of sedentary behaviour in Asian adults: A systematic review

The objective of this study is to systematically review the evidence on correlates of sedentary behaviour (SB) among Asian adults. We searched for studies that examined individual, environmental, and political/cultural correlates of total and domain‐specific SB (transport, occupation, leisure, and screen time) in Asian adults published from 2000 onwards in nine scientific databases. Two reviewers independently screened identified references. Following quality assessment of included studies, we performed narrative synthesis that considered differences based on SB measurements, regions, and population characteristics (PROSPERO: CRD42018095268). We identified 13 249 papers of which we included 49, from four regions and 12 countries. Researchers conducted cross‐sectional analyses and most relied on SB self‐report for SB measurement. Of the 118 correlates studied, the following associations were consistent: higher age, living in an urban area (East Asia), and lower mental health with higher total SB; higher education with higher total and occupational SB; higher income with higher leisure‐time SB; higher transit density with higher total SB in older East Asians; and being an unmarried women with higher SB in the Middle East. We encourage more research in non‐high‐income countries across regions, further exploration of important but neglected correlates using longitudinal designs and qualitative research, and the use of objective instruments to collect SB data.     

唐山市南湖中央生态公园水质质量监测、风险源预警及识别

目的 通过对唐山市南湖中央生态公园湖水水质进行监测和评价,了解南湖水质当前的富营养化和重金属污染状况.方法 选择8个采样点,分别测定温度、pH值、浊度、溶解氧(DO)、化学耗氧量(COD)、五日生化需氧量(BOD530)、总磷(TP)、氨氮、硝酸盐氮、亚硝酸盐氮、汞、砷、铜、锌、镍、铅、镉等指标.结果 各采样点的感官性状均不符合标准,洗星池、养龙水西、养龙水北和青天镜的4个采样点的BOD530均超出国家标准,青天镜的4个采样点的总磷、氨氮、硝酸盐氮均超过国家标准.各采样点其余指标均符合国家标准.单因子污染指数和综合污染指数表明,洗星池的水质最好,综合污染指数为0.27,养龙水的水质仅次于洗星池,综合污染指数的平均值为0.22,这两处均属水质合格的水域.青天镜水质最差,综合污染指数的平均值为1.99,属污染水域.结论 南湖水域的洗星池及养龙水的水质属于水质合格水域,青天镜水质较差,属于污染水域.污染的严重程度为:青天镜＞养龙水＞洗星池.     

Latent trait shared-parameter mixed models for missing ecological momentary assessment data

Latent trait shared-parameter mixed models for ecological momentary assessment (EMA) data containing missing values are developed in which data are collected in an intermittent manner. In such studies, data are often missing due to unanswered prompts. Using item response theory models, a latent trait is used to represent the missing prompts and modeled jointly with a mixed model for bivariate longitudinal outcomes. Both one- and two-parameter latent trait shared-parameter mixed models are presented. These new models offer a unique way to analyze missing EMA data with many response patterns. Here, the proposed models represent missingness via a latent trait that corresponds to the students' “ability” to respond to the prompting device. Data containing more than 10 300 observations from an EMA study involving high school students' positive and negative affects are presented. The latent trait representing missingness was a significant predictor of both positive affect and negative affect outcomes. The models are compared to a missing at random mixed model. A simulation study indicates that the proposed models can provide lower bias and increased efficiency compared to the standard missing at random approach commonly used with intermittent missing longitudinal data.     

Towards an ecological understanding of readiness to engage with interventions for children exposed to domestic violence and abuse: Systematic review and qualitative synthesis of perspectives of children,parents and practitioners

Children who grow up in homes affected by domestic violence and abuse (DVA) are at risk of poor outcomes across the lifespan, yet there is limited evidence on the acceptability and effectiveness of interventions for them. A recent review of child‐focused interventions highlighted a gap in understanding the factors influencing the willingness of parents and children to engage with these programmes. We conducted a systematic review of qualitative evidence on the experiences of receiving and delivering interventions with the aim of identifying factors at different levels of the social–ecological context that may influence parent and child readiness to take up interventions. We searched literature till April 2016 and found 12 reports of eight programmes. Two authors independently screened papers for inclusion, extracted data and identified the first‐ and second‐order constructs. The third‐order constructs were derived and fitted to the ecological framework to inform a picture of readiness to engage with interventions. Three key findings emerged from this review: (a) parent and child readiness is influenced by a complex interplay of individual, relationship and organisational factors, highlighting that individual readiness to take up child‐focussed interventions must be viewed in an ecological context; (b) the specific process through which women become ready to engage in or facilitate child‐focussed interventions may differ from that related to uptake of safety‐promoting behaviours and requires parents to be aware of the impact of DVA on children and to focus on children's needs; (c) there are distinct but interlinked processes through which parents and children reach a point of readiness to engage in an interventions aimed at improving child outcomes. We discuss the implications of these findings for both practice and research.     

Virtual reality measures in neuropsychological assessment: a meta-analytic review

Objective: Virtual reality-based assessment is a new paradigm for neuropsychological evaluation, that might provide an ecological assessment, compared to paper-and-pencil or computerized neuropsychological assessment. Previous research has focused on the use of virtual reality in neuropsychological assessment, but no meta-analysis focused on the sensitivity of virtual reality-based measures of cognitive processes in measuring cognitive processes in various populations. Method: We found eighteen studies that compared the cognitive performance between clinical and healthy controls on virtual reality measures. Results: Based on a random effects model, the results indicated a large effect size in favor of healthy controls (g = .95). For executive functions, memory and visuospatial analysis, subgroup analysis revealed moderate to large effect sizes, with superior performance in the case of healthy controls. Participants’ mean age, type of clinical condition, type of exploration within virtual reality environments, and the presence of distractors were significant moderators. Conclusions: Our findings support the sensitivity of virtual reality-based measures in detecting cognitive impairment. They highlight the possibility of using virtual reality measures for neuropsychological assessment in research applications, as well as in clinical practice.     

An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social–ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social–ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social–ecological models.In recent decades, the world’s biological and physical systems have experienced dramatic change (1, 2). Many marine ecosystems, for example, have undergone abrupt changes known as regime shifts (3, 4). In one prominent case, the Baltic cod fishery suddenly changed in the 1980s from historically high cod biomass and catches (henceforth the “cod boom”) to a sprat-dominant ecosystem with low cod abundance (5–8). This collapse, generally understood to have been precipitated by deteriorating environmental conditions and overfishing (7), had substantial negative socioeconomic impact on Baltic Sea fisheries, including among others the small-scale coastal fishery (9).Ecological analyses of regime shifts, such as of the Baltic cod fishery (10), can capture the complex interplay of ecological and physical processes and drivers that trigger the shift. Numerous studies, however, have shown that understanding individual and collective human behavior is also critical for managing natural resources (11, 12) such as marine ecosystems (13, 14). Social–ecological system research responds to the need to incorporate humans as part of ecosystems by treating natural resource use as arising from linked systems of humans and nature, so-called social–ecological systems. Social–ecological system dynamics result from feedback loops involving biophysical processes, human behavior, and institutional processes within given social and biophysical contexts (15). Formal, quantitative analyses of the contributions of the social and biophysical subsystems to a social–ecological system’s dynamics are rare, however, because knowledge of social–ecological systems is often partial and spread over multiple disciplines (16).Here, we tested the influence of social dynamics on a regime shift in a marine ecosystem using a formal modeling framework. Specifically, we investigated the significance of fisher decision making, as influenced by psychological, economic, and regulatory factors, on the 1980s boom and collapse of the Eastern Baltic cod stock. In a significant advance for natural resource modeling, and for social–ecological modeling more generally, use of the generalized modeling approach (17, 18) enabled us to empirically parameterize, dynamically model, and analyze the qualitative social and ecological dynamics of the Baltic cod fishery at comparable levels of detail and without detailed specification of causal relationships. The Baltic cod fishery was selected because the ecological dynamics during the cod boom and collapse have been well-studied (10, 19, 20), and information about fisher behavior and institutional settings, such as regulation and subsidy policy, is available. Additionally, the cod boom and collapse are qualitatively distinct features of the social–ecological system’s dynamics that are amenable to the concepts and methods of dynamical systems theory (21), such as stability.     

Genetic specificity of a plant–insect food web: Implications for linking genetic variation to network complexity

Theory predicts that intraspecific genetic variation can increase the complexity of an ecological network. To date, however, we are lacking empirical knowledge of the extent to which genetic variation determines the assembly of ecological networks, as well as how the gain or loss of genetic variation will affect network structure. To address this knowledge gap, we used a common garden experiment to quantify the extent to which heritable trait variation in a host plant determines the assembly of its associated insect food web (network of trophic interactions). We then used a resampling procedure to simulate the additive effects of genetic variation on overall food-web complexity. We found that trait variation among host-plant genotypes was associated with resistance to insect herbivores, which indirectly affected interactions between herbivores and their insect parasitoids. Direct and indirect genetic effects resulted in distinct compositions of trophic interactions associated with each host-plant genotype. Moreover, our simulations suggest that food-web complexity would increase by 20% over the range of genetic variation in the experimental population of host plants. Taken together, our results indicate that intraspecific genetic variation can play a key role in structuring ecological networks, which may in turn affect network persistence.Network theory has provided both a conceptual and a quantitative approach for mapping interactions between species and making predictions about how the gain or loss of species will affect the structure and dynamics of ecological networks (1–3). Representing a network at the species level, however, makes the implicit assumption that each species consists of a homogenous population of individuals, all of which interact equally with individuals of different species. However, most populations are heterogeneous mixtures of individuals that vary in their phenotypes, and there is growing evidence that this intraspecific variation is an important factor governing the assembly of ecological communities (4–6). Consequently, there is a clear need to account for the role of intraspecific variation in structuring ecological networks (7).Genetic variation is a key driver of intraspecific variation and many studies have now demonstrated direct and indirect genetic effects on species interactions (8–10) and the composition of communities across multiple trophic levels (11–14). This prior work forms a clear expectation that intraspecific genetic variation is capable of scaling up to affect the structure of an ecological network. In particular, we expect that network structure will be affected by genetic variation through at least two different mechanisms. For a food web (network of trophic interactions), genetic variation in the quality of a basal resource may alter the (i) abundances or (ii) phenotypes of consumer species or both (15). These direct genetic effects on consumers may then have cascading effects on the strength of trophic interactions between consumers and their predators (15), resulting in distinct compositions of trophic interactions associated with different genotypes of the basal resource (Fig. 1). If such genetic specificity in the composition of trophic interactions occurs, then theory predicts that increasing genetic variation will result in more interactions per species (6, 16) and therefore greater food-web complexity (Fig. 2). Moreover, greater complexity may in turn affect food-web dynamics, as more complex food webs are predicted to be more robust to species extinctions (3, 17). However, whether genetic variation is capable of scaling up to affect food-web complexity is currently unclear.Open in a separate windowFig. 1.Genetic specificity of trophic interactions in a plant–insect food web. The species comprising the food web in this study include a host plant (coastal willow, S. hookeriana), four herbivorous galling insects, and six insect parasitoids (species details in Materials and Methods). The plant–insect food web consists of 16 trophic interactions (4 willow–gall and 12 gall–parasitoid) aggregated from all plant individuals sampled in this common garden experiment, whereas each genotype subweb represents the trophic interactions aggregated from all plant individuals of the corresponding genotype. We depicted three genotype subwebs (of 26) to illustrate the differences in trophic interactions associated with each willow genotype. The width of each gray segment is proportional to the number of individuals associated with each trophic interaction. Note that we scaled the width of trophic interactions to be comparable among genotype subwebs, but not between subwebs and the aggregated food web, to emphasize the differences among subwebs.Open in a separate windowFig. 2.Conceptual model of how increasing genetic variation (number of shades of green circles) results in greater food-web complexity (number of interactions per species). If different genotypes of a basal resource are associated with distinct compositions of trophic interactions (i.e., genetic specificity of trophic interactions), then increasing genetic variation in the resource will result in a more complex food web because of the increase in the number of interactions per species at all three trophic levels. Colors correspond to different trophic levels (green, basal resource; blue, primary consumer; orange, secondary consumer), whereas different shapes within each trophic level correspond to different species.In this study, we quantify the genetic specificity of trophic interactions and use these data to simulate the additive effects of genetic variation on food-web complexity. To do this, we used a common garden experiment of a host plant (26 genotypes of coastal willow, Salix hookeriana) and its associated food web of insect galls and parasitoids (Fig. 1). We focused on this plant–insect food web for three reasons. First, we have demonstrated in previous work that S. hookeriana (hereafter, willow) displays heritable variation in traits associated with leaf quality (36 traits, mean H² = 0.72) and plant architecture (4 traits, mean H² = 0.27), some of which are also associated with resistance to its community of galling herbivores (18). Second, the unique biology of galling insects makes them ideal for building quantitative food webs. In particular, galls provide a refuge for larva from attack by most generalist predators (19); therefore, galls and their natural enemies often form a distinct subset of the larger food web associated with host plants. In our system, all of the natural enemies are insect parasitoids that complete their development within the gall after parasitizing larva, making it easy to identify and quantify all of the trophic interactions within this food web. Third, the biology of galls is also ideal for identifying the mechanisms mediating trophic interactions. In particular, gall size is a key trait that affects the ability of parasitoids to successfully oviposit through the gall wall and into the larva within the gall (i.e., larger galls provide a refuge from parasitism) (20). Moreover, gall size is determined, in part, by the genotype of the plant (20), so we have a clear mechanism by which genetic variation can affect the strength of trophic interactions. Taken together, our study seeks to examine how intraspecific genetic variation influences the structure of ecological networks. In doing so, our study takes a crucial step toward a more predictive understanding of how the gain or loss of genetic variation will affect the dynamics of ecological networks.     

Thermal niches of planktonic foraminifera are static throughout glacial–interglacial climate change

Abiotic niche lability reduces extinction risk by allowing species to adapt to changing environmental conditions in situ. In contrast, species with static niches must keep pace with the velocity of climate change as they track suitable habitat. The rate and frequency of niche lability have been studied on human timescales (months to decades) and geological timescales (millions of years), but lability on intermediate timescales (millennia) remains largely uninvestigated. Here, we quantified abiotic niche lability at 8-ka resolution across the last 700 ka of glacial–interglacial climate fluctuations, using the exceptionally well-known fossil record of planktonic foraminifera coupled with Atmosphere–Ocean Global Climate Model reconstructions of paleoclimate. We tracked foraminiferal niches through time along the univariate axis of mean annual temperature, measured both at the sea surface and at species’ depth habitats. Species’ temperature preferences were uncoupled from the global temperature regime, undermining a hypothesis of local adaptation to changing environmental conditions. Furthermore, intraspecific niches were equally similar through time, regardless of climate change magnitude on short timescales (8 ka) and across contrasts of glacial and interglacial extremes. Evolutionary trait models fitted to time series of occupied temperature values supported widespread niche stasis above randomly wandering or directional change. Ecotype explained little variation in species-level differences in niche lability after accounting for evolutionary relatedness. Together, these results suggest that warming and ocean acidification over the next hundreds to thousands of years could redistribute and reduce populations of foraminifera and other calcifying plankton, which are primary components of marine food webs and biogeochemical cycles.

Abiotic niche dynamics determine patterns of community composition over space and regulate trajectories of diversity over time (1). Both niche lability (2, 3) and conservatism (1, 4) have been proposed to spur speciation, and abiotic niche lability has been associated with ecological invasions (5–7) and with reduced risk of extinction during times of climate change (8). Thus, a deeper understanding of species’ propensity for niche stasis versus lability could improve predictions of biodiversity restructuring in response to anthropogenic climate change (9).Stasis in species’ abiotic niches through time has been documented in empirical research, but most such studies have been limited to ecological niche modeling on decadal scales (reviewed in ref. 10) or paleoecological examination on 10⁶ to 10⁷ y scales (5, 11, 12). Since empirical rates of niche change are scarce and difficult to acquire, many studies merely assume that niche evolution occurs at a constant rate along branches of a phylogeny (2, 3, 6, 7). Niche dynamics at intermediate timescales of centuries to millennia are particularly poorly documented (10), and studies at this meso scale have been restricted to terrestrial systems (e.g., refs. 13–15) or to comparisons between the present day and the single historical time step of the Last Glacial Maximum, ∼21 ka (16–20). Quantifying the rate and relative frequency of niche change in marine species over timescales of 10² to 10⁵ years is important, however, because species will adapt or go extinct in response to anthropogenic ocean changes over this timescale (21).Here, we investigated climatic niche lability from the rich sedimentary archive of global planktonic foraminifera across the last 700 ka of glacial–interglacial cycles at 8-ka resolution. Planktonic foraminifera (Protista) construct “shells” (tests) of calcite, thereby sequestering carbon and recording an isotopic signature of past ocean conditions. Tests readily accumulate over large expanses of the seafloor. Consequently, the fossil record of foraminifera—arguably “the best fossil record on Earth” (22)—affords an exceptionally high-resolution view into past species distributions. This detailed record fuels studies of biostratigraphy, paleoclimatology, and paleoecology (20, 22–25). Moreover, the complete species diversity of planktonic foraminifera has been described for the Plio–Pleistocene, with good agreement between morphological and molecular phylogenies (22, 25–27). Although some have speculated that foraminifera competitively exclude each other (24), recent work found that planktonic foraminifera species seldom restrict each other’s distributions (28). Presumably, therefore, species occupy the full envelope of existing environmental conditions within their tolerance limits, and geographic distributions are determined almost entirely by physical ocean conditions.We developed five analyses to investigate the degree of abiotic niche lability in foraminifera. All methods examined the univariate niche axis of temperature, which is the single most important explanatory variable in regard to geographic distributions of foraminifera (20, 29–32) and is a climate-related stressor and extinction driver for diverse marine fauna across timescales (33, 34). The adaptive potential of thermal niches has been taken as a key determinant of global community structure and genetic connectance in plankton (35). Primary productivity and other environmental variables, however, may also structure abiotic niches of plankton (36). Our suite of analyses quantified whether and by how much planktonic foraminiferal niches shifted along a temperature axis. First, we correlated time series of species’ thermal optima with global temperature to determine whether species tracked suitable habitat or experienced environmental fluctuations in situ. We then quantified species’ niche dissimilarity between pairs of time bins—either tracking niches across bin boundaries or contrasting niches at climatic extremes of glacial maxima and interglacial thermal peaks. To characterize niche change we applied trait evolution models to time series of temperatures at occupied sites. Lastly, we explored variation in intraspecific niche lability among ecotypes while accounting for phylogenetic relatedness. SI Appendix, Table S1 lists the response variable and sample size for each analysis.     

A test of the chromosomal theory of ecotypic speciation in Anopheles gambiae

The role of chromosomal inversions in speciation has long been of interest to evolutionists. Recent quantitative modeling has stimulated reconsideration of previous conceptual models for chromosomal speciation. Anopheles gambiae, the most important vector of human malaria, carries abundant chromosomal inversion polymorphism nonrandomly associated with ecotypes that mate assortatively. Here, we consider the potential role of paracentric inversions in promoting speciation in A. gambiae via "ecotypification," a term that refers to differentiation arising from local adaptation. In particular, we focus on the Bamako form, an ecotype characterized by low inversion polymorphism and fixation of an inversion, 2Rj, that is very rare or absent in all other forms of A. gambiae. The Bamako form has a restricted distribution by the upper Niger River and its tributaries that is associated with a distinctive type of larval habitat, laterite rock pools, hypothesized to be its optimal breeding site. We first present computer simulations to investigate whether the population dynamics of A. gambiae are consistent with chromosomal speciation by ecotypification. The models are parameterized using field observations on the various forms of A. gambiae that exist in Mali, West Africa. We then report on the distribution of larvae of this species collected from rock pools and more characteristic breeding sites nearby. Both the simulations and field observations support the thesis that speciation by ecotypification is occurring, or has occurred, prompting consideration of Bamako as an independent species.     

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.Amazonia consists of 815 million ha of rainforest, transitional forest, and tropical savannahs; stores approximately half of tropical forest carbon (1); and plays a vital role in global water, energy, and carbon cycling (2). Although uncertainties in climate predictions for the region remain large (3), recent analyses imply that significant portions of the basin will experience both longer and more intense dry seasons by the end of the 21st century (3–6). There is particular concern about southern Amazonian forests that experience longer dry seasons than forests in central and western Amazonia (3) and where a trend of increasing dry season length (DSL) and intensity has already been observed (7). Despite the importance of this region for regional and global climate, the climate sensitivity of the Amazon forests remains uncertain: model predictions range from a large-scale die-back of the Amazon (8, 9) to predictions that the biome will remain largely intact, and may even increase in biomass (10–12). Although some of these differences can be attributed to differences in the predicted future climate forcing of the region (13, 14), accurate predictions of how changes in climate will affect Amazonian forests also rely on an accurate characterization of how the ecosystem is affected by a given change in climate forcing. In this study, we examine the climate sensitivity of the Amazon ecosystem, focusing on the mechanisms underpinning changes in forest dynamics and their implications for the timing and nature of basin-wide shifts in biomass in response to a drying climate.Variation in forest biomass across the Amazon basin (15–17) has been shown to correlate with DSL (16–18) (Fig. 1), soil texture (16), shifts in stem turnover rate (19), and forest composition (20). In general, high-biomass moist tropical forests occur where DSL, defined here as the number of months in which precipitation is <100 mm (6, 9), is short, and low-biomass, savannah-like ecosystems are primarily found when DSLs are long (Fig. 1A). In addition, a significant relationship is observed between regional-scale spatial heterogeneity in above-ground biomass (AGB > 2 kg of carbon per square meter) and DSL, with drier places having greater spatial heterogeneity: This pattern is seen both at the scale of 1° (Fig. 1C; r² = 0.88, P < 0.01 for remote sensing-based AGB estimates) and at smaller spatial scales (SI Appendix, section S1). In other words, in moist areas, where DSL is short, forests have relatively homogeneous levels of AGB, whereas in drier areas, forests are increasingly heterogeneous. As we show below, this observed heterogeneity in response to increasing DSL has important implications for how the structure, composition, and dynamics of Amazon forests will be affected by changes in climate.Open in a separate windowFig. 1.(A) Change in AGB with DSL for remote sensing-based estimates (black and gray circles), ground-based plot measurements (blue triangles), ED2 model output (green circles), and ED2-BL model output (purple circles). (B) Distribution of AGB in the observations and the two models. (C) Change in the percentage of biomass variability, with the coefficient of variation (CV) defined as 1σ/mean. Results are for undisturbed primary vegetation forests. Data are from Baccini et al. (1), Saatchi et al. (48), and Baker et al. (20, 49).The Ecosystem Demography Biosphere (ED2) model, a process-based terrestrial biosphere model that represents individual plant-level dynamics, including competition for light and water (21, 22), was used to investigate the impact of ecosystem heterogeneity on the Amazon forest’s ecological resilience to climate perturbations (SI Appendix, section S3). Here, the term “ecological resilience” is used to describe the ability of a forest to maintain fundamental characteristics, such as carbon pools, composition, and structure, despite changes in climate (23). ED2 model simulations for the Amazon region, forced with a regional climate dataset derived from in situ measurements and remote-sensing observations, correctly reproduce the observed pattern of AGB variability as a function of DSL and soil texture (Fig. 1 and SI Appendix, section S4). In addition, ED2 model simulations for sites with detailed ground-based soil texture, forest structure, turnover, and composition measurements are also consistent with the observed patterns of variation in these quantities (SI Appendix, section S4).An ensemble of model simulations with varying soil texture was used to investigate the mechanisms that underpin the observed variable response to increasing DSL (SI Appendix, section S3). In the model, individual plant productivity is modified by a measure of plant water stress (γ_WS) that integrates soil texture, precipitation, and plant transpiration demand such that, as γ_WS increases, the plants close their stomata to reduce water loss. In the ED2 ensemble simulations, plot biomass is highly correlated with the average γ_WS for the forested sites (defined here as AGB > 3 kg of carbon per square meter) (Fig. 2C; r² = 0.96–0.99, P < 0.01; SI Appendix, section S5). Associated with changes in AGB that occur as water stress increases are correlated changes in the productivity and composition of the plant canopy (SI Appendix, section S6).Open in a separate windowFig. 2.Impact of changes in soil clay fraction (A and B) and plant water stress (C and D) on AGB in the ED2 (A and C) and ED2-BL (B and D) model simulations. Four climatological conditions are shown, a 2-month dry season, a 4-month dry season, a 6-month dry season, and an 8-month dry season.The important role that water stress operating at the scale of individual plants plays in generating these responses is illustrated by comparing the native ED2 model predictions with output from a horizontally and vertically averaged version of the model (ED2-BL), analogous to a conventional “big leaf” terrestrial biosphere model that represents the canopy in an aggregated manner (SI Appendix, section S3). In the ED2-BL simulations, there is no significant relationship between the spatial heterogeneity of forested sites and DSL (Fig. 1 A and C; r² = 0.24, P = 0.32). The absence of individual-level plant dynamics in the ED2-BL model results in a markedly different response to variations in soil texture and DSL than the native model formulation: Biomass initially declines as a function of increasing water stress, but a tipping point is then reached, beyond which the high-biomass forest is no longer stable and is replaced by a low-biomass savannah (Fig. 2). The result is a bimodal distribution of AGB across the basin in the ED2-BL model simulations, in contrast to the continuous distribution seen in the native model formulation and the observations (Fig. 1B). This response mirrors the response seen in other big-leaf-type ecosystem models (9). In native ED2 simulations, when water stress is prevented from influencing plant productivity, DSL and soil texture no longer have an impact on AGB (SI Appendix, section S5 and Fig. S5). Taken together, these simulations indicate that the driving mechanism behind the observed heterogeneous response to changes in DSL is the differential performance of individuals within the canopy to declining water availability, and how this response is modulated by soils with different hydrological properties. Specifically, the size and age structure of the ED2 plant canopy results in individuals’ differential access to both light and soil water, influencing the dynamics of individual plant growth and mortality (SI Appendix, section S6). Due to the nonlinear nature of functions governing plant growth, mortality, and recruitment, this heterogeneity results in a more continuous, graded response to changes in water stress than the big leaf (ED2-BL) formulation (Fig. 2). The consequence of this heterogeneity in plant-level responses to changes in soil moisture is that soil texture is likely to become increasingly important for controlling AGB as DSL increases. Soil fertility gradients also influence Amazonian AGB (16–18); however, as we show in SI Appendix, section S2, they do not account for the observed regional-scale pattern of increasing biomass heterogeneity with increasing DSL.The ED2 biosphere model was used to investigate the expected patterns and time scales of Amazonian ecosystem response to a 1- to 4-month change in DSL over the 21st century (6). Earlier analyses have suggested that by accurately representing the dynamics of individual trees, models such as ED2 that incorporate plant-level dynamics are likely to provide more realistic estimates of forest successional change (21). Forests with a 4-month dry season (24% of the Amazon basin) are projected to lose ∼20% of their biomass with a 2-month increase in DSL (range of 11–58% loss of AGB dependent on clay content), whereas drier forests (6-month DSL) respond more rapidly to changes in climate, losing ∼29% (20–37% loss dependent on clay content) of their biomass with a 1-mo increase in DSL (Fig. 3A and SI Appendix, section S7). As the forests adjust to the new climate regime, the spatial heterogeneity of forest structure, composition, and biomass across the range of soil textures gradually increase. As seen in Fig. 3B, the model predicts that forests in soils with low clay content will be relatively unaffected by the change in climate regime; however, in soils with high clay content, the increase in levels of water stress caused by the onset of a longer dry season will result in marked changes in forest AGB and composition, beginning approximately 3 years after the perturbation (Fig. 3C). The time scale of the predicted initial ecosystem response is consistent with the results from two field-based through-fall exclusion experiments, which showed declining biomass 3–4 years after a drought was introduced (24, 25). Underlying these predicted changes in AGB and canopy composition are reductions in plant growth and increases in mortality rates (SI Appendix, Figs. S14 and S15). Whereas the majority of the change in AGB occurs in the first 100 y, the composition and structure of the forest continue to reorganize for more than 200 years after the perturbation (Fig. 3C). Specifically, the simulations predict a substantial decline in the abundance of late-successional trees in soils with high clay content. This prediction arises as a consequence of the slower rate of growth of late-successional trees that makes them more vulnerable to water stress-induced increases in mortality rates and less competitive against mid-successional species that are favored by drought-induced increases in understory light levels. This prediction of increased vulnerability of late-successional trees to increases in water stress is as yet untested; however, more generally, our analysis highlights how shifts in climate forcing are likely to drive significant shifts in tropical forest composition and structure over decadal and centennial time scales.Open in a separate windowFig. 3.Predicted response of forest AGB and composition to an increase in DSL. (A) Change in AGB after 100 y as a result of increasing DSL for forests with historic DSLs of 2, 4, and 6 months for the range of soil textures simulated in the ensemble model simulations (n = 30). The magnitude of the change in AGB is influenced by soil clay fraction: The mean (solid line), 1σ deviation (shaded region), and minimum and maximum values (dashed lines) are shown. (B and C) Bar plots illustrating the impact of a 2-month increase in dry season (from 4 to 6 months) on a forest situated on a low clay content soil and a forest situated on a high clay content soil. The color of the bars indicates the contribution of mid- and late-successional trees, illustrating the shift in composition caused by the increase in DSL.Recent work has hypothesized that two stable ecosystem states may exist along the boundaries of tropical forests and that a tipping point may occur once a climatological moisture threshold is passed (26, 27). Instead, by combining field observations, remote-sensing estimates, and a terrestrial biosphere model, we find no evidence that an irreversible rapid transition or dieback of Amazon forests will occur in response to a drying climate (8, 9) or that forests will be unresponsive (11, 12). Rather, our results suggest that, at least in the case of Amazonian forests, the ecosystem will exhibit an immediate but heterogeneous response to changes in its climate forcing and that a continuum of transitional forest ecosystem states exists. These conclusions are consistent with experimental observations across Amazonia of short-term drought impacts (28). Furthermore, we find that future climate-induced shifts between a moist tropical forest and a dry forest will be a more graded transition accompanied by increasing spatial heterogeneity in forest AGB, composition, and dynamics across gradients in soil texture. The ability of Amazonian forests to undergo reorganization of their structure and composition in response to climate-induced changes in levels of plant water stress acts as an important buffer against more drastic threshold changes in vegetation state that would otherwise occur; however, it also means that the forests are more sensitive to smaller magnitude changes in their climate forcing than previous studies have suggested.The analysis conducted here intentionally focused on the direct impacts of changes in climate forcing on vegetation, and did not incorporate the effects of soil nutrients, climate-driven changes in fire frequency, the effects of increasing atmospheric CO₂ concentrations, the impacts of land transformation, and biosphere/atmosphere feedbacks. With regard to soil nutrients, at the basin scale, analyses indicate that forest composition, structure, biomass, and dynamics also vary across a gradient in soil fertility (16, 17), with the younger, more fertile soils of western Amazonia supporting forests with lower AGB and higher rates of biomass productivity and stem turnover relative to the forests of the central Amazon and Guianan Shield, which are located on older, more nutrient-poor soils. Meanwhile, landscape-scale studies in central (29) and northwestern (30) Amazonia have found that more fertile clay soils have higher AGB than nutrient-poor sandy soils. Further discussion of the impact of soil nutrients can be found in SI Appendix, section S2).Plant water availability is affected by both the hydraulic properties of soils and plant hydraulic architecture. Our findings of the importance of individual plant water stress on forest response to changes in climate highlight the need for additional studies into these two important, but relatively understudied, properties of tropical forests. With regard to soil hydraulic properties, recent studies suggest that the relationship between a soil’s texture and its hydraulic properties may differ significantly between tropical and temperate soils (31, 32). However, the impact of these differences on plant water availability remains uncertain. With regard to plant hydraulic architecture, although some measurements exist on rooting properties and vascular architecture of tropical trees (33–36), the above- and below-ground hydraulic attributes of tropical trees remain poorly characterized, especially compared with the hydraulic attributes of their temperate counterparts.In some areas, particularly those areas with long dry seasons, increasing water stress is likely to be accompanied by increases in fire frequency, which may act to generate more rapid transitions from a higher biomass forested state to a more savannah-like biome (26, 27). Because these two mechanisms have distinct impacts on forest composition, structure, and function, both must be considered when predicting future responses to changes in climate. The potential impacts of fire on patterns of ecosystem change are discussed in SI Appendix, section S1. Recent modeling studies indicate that CO₂ fertilization may mitigate the impact of increasing water stress (37); however, experimental studies are needed to quantify the impact of elevated CO₂ concentrations better on the physiological functioning of Amazon trees.Although regional patterns of Amazonian AGB are complex, reflecting the impact of multiple factors, our results suggest that plant-level responses to soil texture heterogeneity and changes in DSL are important in explaining the observed basin-wide pattern of variation in Amazonian AGB, providing a mechanistic explanation for the observed correlations between DSL, AGB, and changes in stand structure and composition (16, 17). These conclusions may also apply to African and Asian tropical forests; however, important differences exist in the future climate predictions for these regions (38) and their soil edaphic and nutrient characteristics and historical fire regimes (39–41).The response of forests to changes in their climate forcing is an emergent ecosystem-level response that is ultimately driven by individual trees responding to changes in their local environments. Nonlinearities in the performance of individual plants, such as their rates of photosynthetic assimilation and mortality, as environmental conditions change imply that terrestrial biosphere models need to represent these differential responses of individuals to capture emergent ecosystem properties accurately (42). This analysis demonstrates that the conventional approach of modeling average plants in average environments within climatological grid cells underestimates the direct, near-term response of tropical forests to climatological change but overestimates the direct impacts of larger scale changes in forcing. Consequently, accurate predictions for the timing and nature of forest responses to changes in climate require consideration of how climate and soils affect the performance of individuals within plant canopies. As we have shown here, models that incorporate plant-level dynamics are able to characterize observed extant patterns of variation in the structure, composition, and dynamics of Amazonian ecosystems more accurately, and accounting for these patterns has important implications for the sensitivity and ecological resilience of Amazon forests to different levels of climatological perturbation.